mridulm commented on a change in pull request #30691:
URL: https://github.com/apache/spark/pull/30691#discussion_r629811689
##########
File path: core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
##########
@@ -2004,6 +2020,131 @@ private[spark] class DAGScheduler(
}
}
+ /**
+ * Schedules shuffle merge finalize.
+ */
+ private[scheduler] def scheduleShuffleMergeFinalize(stage: ShuffleMapStage):
Unit = {
+ logInfo(("%s (%s) scheduled for finalizing" +
+ " shuffle merge in %s s").format(stage, stage.name,
shuffleMergeFinalizeWaitSec))
+ shuffleMergeFinalizeScheduler.schedule(
+ new Runnable {
+ override def run(): Unit = finalizeShuffleMerge(stage)
+ },
+ shuffleMergeFinalizeWaitSec,
+ TimeUnit.SECONDS
+ )
+ }
+
+ /**
+ * DAGScheduler notifies all the remote shuffle services chosen to serve
shuffle merge request for
+ * the given shuffle map stage to finalize the shuffle merge process for
this shuffle. This is
+ * invoked in a separate thread to reduce the impact on the DAGScheduler
main thread, as the
+ * scheduler might need to talk to 1000s of shuffle services to finalize
shuffle merge.
+ */
+ private[scheduler] def finalizeShuffleMerge(stage: ShuffleMapStage): Unit = {
+ logInfo("%s (%s) finalizing the shuffle merge".format(stage, stage.name))
+ externalShuffleClient.foreach { shuffleClient =>
+ val shuffleId = stage.shuffleDep.shuffleId
+ val numMergers = stage.shuffleDep.getMergerLocs.length
+ val numResponses = new AtomicInteger()
+ val results = (0 until numMergers).map(_ =>
SettableFuture.create[Boolean]())
+ val timedOut = new AtomicBoolean()
+
+ def increaseAndCheckResponseCount(): Unit = {
+ if (numResponses.incrementAndGet() == numMergers) {
+ logInfo("%s (%s) shuffle merge finalized".format(stage, stage.name))
+ // Since this runs in the netty client thread and is outside of
DAGScheduler
+ // event loop, we only post ShuffleMergeFinalized event into the
event queue.
+ // The processing of this event should be done inside the event
loop, so it
+ // can safely modify scheduler's internal state.
+ eventProcessLoop.post(ShuffleMergeFinalized(stage))
+ }
+ }
+
+ stage.shuffleDep.getMergerLocs.zipWithIndex.foreach {
+ case (shuffleServiceLoc, index) =>
+ // Sends async request to shuffle service to finalize shuffle merge
on that host
+ shuffleClient.finalizeShuffleMerge(shuffleServiceLoc.host,
+ shuffleServiceLoc.port, shuffleId,
+ new MergeFinalizerListener {
+ override def onShuffleMergeSuccess(statuses: MergeStatuses):
Unit = {
+ assert(shuffleId == statuses.shuffleId)
+ // Register the merge results even if already timed out, in
case the reducer
+ // needing this merged block starts after dag scheduler
receives this response.
+ mapOutputTracker.registerMergeResults(statuses.shuffleId,
+ MergeStatus.convertMergeStatusesToMergeStatusArr(statuses,
shuffleServiceLoc))
+ if (!timedOut.get()) {
+ increaseAndCheckResponseCount
+ results(index).set(true)
+ }
+ }
+
+ override def onShuffleMergeFailure(e: Throwable): Unit = {
+ if (!timedOut.get()) {
+ logWarning(s"Exception encountered when trying to finalize
shuffle " +
+ s"merge on ${shuffleServiceLoc.host} for shuffle
$shuffleId", e)
+ increaseAndCheckResponseCount
+ // Do not fail the future as this would cause dag scheduler
to prematurely
+ // give up on waiting for merge results from the remaining
shuffle services
+ // if one fails
+ results(index).set(false)
+ }
+ }
+ })
+ }
+ // DAGScheduler only waits for a limited amount of time for the merge
results.
+ // It will attempt to submit the next stage(s) irrespective of whether
merge results
+ // from all shuffle services are received or not.
+ // TODO: SPARK-33701: Instead of waiting for a constant amount of time
for finalization
+ // TODO: for all the stages, adaptively tune timeout for merge
finalization
+ try {
+ Futures.allAsList(results: _*).get(shuffleMergeResultsTimeoutSec,
TimeUnit.SECONDS)
+ } catch {
+ case _: TimeoutException =>
+ logInfo(s"Timed out on waiting for merge results from all " +
+ s"$numMergers mergers for shuffle $shuffleId")
+ timedOut.set(true)
+ eventProcessLoop.post(ShuffleMergeFinalized(stage))
+ }
+ }
+ }
+
+ private def processShuffleMapStageCompletion(shuffleStage: ShuffleMapStage):
Unit = {
+ markStageAsFinished(shuffleStage)
+ logInfo("looking for newly runnable stages")
+ logInfo("running: " + runningStages)
+ logInfo("waiting: " + waitingStages)
+ logInfo("failed: " + failedStages)
+
+ // This call to increment the epoch may not be strictly necessary, but it
is retained
+ // for now in order to minimize the changes in behavior from an earlier
version of the
+ // code. This existing behavior of always incrementing the epoch following
any
+ // successful shuffle map stage completion may have benefits by causing
unneeded
+ // cached map outputs to be cleaned up earlier on executors. In the future
we can
+ // consider removing this call, but this will require some extra
investigation.
+ // See https://github.com/apache/spark/pull/17955/files#r117385673 for
more details.
+ mapOutputTracker.incrementEpoch()
+
+ clearCacheLocs()
+
+ if (!shuffleStage.isAvailable) {
+ // Some tasks had failed; let's resubmit this shuffleStage.
+ // TODO: Lower-level scheduler should also deal with this
+ logInfo("Resubmitting " + shuffleStage + " (" + shuffleStage.name +
+ ") because some of its tasks had failed: " +
+ shuffleStage.findMissingPartitions().mkString(", "))
+ submitStage(shuffleStage)
+ } else {
+ markMapStageJobsAsFinished(shuffleStage)
+ submitWaitingChildStages(shuffleStage)
+ }
+ }
+
+ private[scheduler] def handleShuffleMergeFinalized(stage: ShuffleMapStage):
Unit = {
+ stage.shuffleDep.markShuffleMergeFinalized
Review comment:
`markShuffleMergeFinalized` -> `markShuffleMergeFinalized()`
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
[email protected]
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
